Xingjian Bai

Undergraduate @ Oxford

Incoming PhD student @ MIT

Email: xbai AT mit.edu

I am an undergraduate student at Oxford, studying Mathematics and Computer Science. With some research experience in online algorithms and generative models, my research primarily explores a blend of classical algorithms and machine learning, including topics like learning-augmented algorithms and the theoretical studies of machine learning models. I am driven by projects that have the potential to make a scientific impact.

During my time at Oxford, I have had the privilege of working with Jan Obloj, Christian Coester, Christian Rupprecht, and Luke Melas-Kyriazi. I also spent a rewarding summer at Stanford, collaborating with Jiajun Wu, Weiyu Liu, and Joy Hsu. Outside of my academic pursuits, I enjoy jogging and playing tennis. I also engage in programming competitions.

Collaborators: I am eager to learn from and collaborate with individuals from diverse backgrounds. If you would like to discuss something, please don’t hesitate to reach out! You can contact me via email or schedule a time to chat through Chatting Time.

News:

Feb 2024: Our paper, Fixed Point Diffusion Models, is accepted at CVPR'24!

Unweighted Layered Graph Traversal

Xingjian Bai, Christian Coester, Romain Cosson

In submission

Paper

@misc{bai2024unweighted,
      title={Unweighted Layered Graph Traversal}, 
      author={Xingjian Bai and Christian Coester and Romain Cosson},
      year={2024},
      eprint={2404.16176},
      archivePrefix={arXiv},
      primaryClass={cs.DS}
}

Fixed Point Diffusion Models

Xingjian Bai*, Luke Melas-Kyriazi*

(*equal contribution)

CVPR 2024

Page

Paper

Code

@InProceedings{bai2024fixed,
    title={Fixed Point Diffusion Models},
    author={Xingjian Bai and Luke Melas-Kyriazi},
    booktitle = {CVPR},
    year = {2024}
}

Goodhart's Law in Reinforcement Learning

Jacek Karwowski, Oliver Hayman, Xingjian Bai, Charlie Griffin, Joar Skalse

ICLR 2023

Paper

@InProceedings{karwowski2023goodharts,
    title={Goodhart's Law in Reinforcement Learning}, 
    author={Jacek Karwowski and Oliver Hayman and Xingjian Bai and Klaus Kiendlhofer and Charlie Griffin and Joar Skalse},
    year={2024},
    booktitle = {ICLR},
}

Sorting with Predictions

Xingjian Bai, Christian Coester

NeurIPS 2023

Paper

Poster

Code

@InProceedings{bai2023sorting,
    title={Sorting with Predictions}, 
    author={Xingjian Bai and Christian Coester},
    booktitle = {NeurIPS},
    year = {2023}
}

Wasserstein Distributional Robustness of Neural Networks

Xingjian Bai, Guangyi He, Yifan Jiang, Jan Obloj

NeurIPS 2023

Paper

Poster

Code

@InProceedings{bai2023wasserstein,
    title={Wasserstein distributional robustness of neural networks}, 
    author={Xingjian Bai and Guangyi He and Yifan Jiang and Jan Obloj},
    year={2023},
    booktitle = {NeurIPS},
}

Xingjian Bai

PUBLICATIONS

Unweighted Layered Graph Traversal

Fixed Point Diffusion Models

Goodhart's Law in Reinforcement Learning

Sorting with Predictions

Wasserstein Distributional Robustness of Neural Networks

CHATTING TIME